The Automated Library Robot
August 11, 2016
Libraries have evolved from centers that allow people to borrow books and conduct research to a one-stop shop for Internet usage. People love to say that libraries are useless and only archive outmoded knowledge, but they still provide useful services for people and cannot be easily replicated with a machine. Science Daily shares that “High-Tech Librarian Knows Its Books” and relates how robotics are entering libraries.
No, an automated machine is not replacing librarians, but one of the biggest problems that libraries face are disorderly books. It is the bane of libraries everywhere and it makes librarians want to weep when a clean, orderly shelf is messed up within minutes by a lackadaisical hands. It takes a lot of hours and staff to keep shelves in order, time that could be better spent doing something else:
“At A*STAR’s Institute for Infocomm Research, researchers Renjun Li, Zhiyong Huang, Ernest Kurniawan, and Chin Keong Ho are designing robots that can relieve librarians of many menial tasks, while enhancing searching and sorting of books. Their latest project is an autonomous robotic shelf scanning (AuRoSS) platform that can self-navigate through libraries at night, scanning RFID tags to produce reports on missing and out-of-sequence books.”
Taking away this task will save some time and even locate missing materials with (perhaps) more accuracy than a human. Robots will not be destroying this sacred institution of knowledge, only improving it. Budget crunches are a bigger problem for libraries than being replaced by robots.
Whitney Grace, August 11, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
There is a Louisville, Kentucky Hidden /Dark Web meet up on August 23, 2016.
Information is at this link: https://www.meetup.com/Louisville-Hidden-Dark-Web-Meetup/events/233019199/
Quote to Note: Big Data Governance
August 10, 2016
I read an interview with a wizard from Talend, which I did not know had French roots. The write up is “Interview: Christophe Toum, Talend on Why Big Data Needs Big Governance.” I noted two passages which I found refreshing.
The first address the unpleasant topic of being organized. The code word for this all-too-human characteristic is “governance.” I highlighted this passage:
At Talend we believe Big Data without governance will quickly become a big problem…Big Data needs even more governance.
My view is that more of an annoying administrative, human subject matter intensive investment required, the less governance will be applied. Just a thought based on my experience.
The second comment elicited one exclamation report from my subdued pale blue highlighter:
Controlling who can access and use this data, what data is verified and trusted, by whom and how, is a big deal.
No kidding.
Stephen E Arnold, August 10, 2016
WCC and Elm Developers
August 10, 2016
WCC is a specialist search and content processing company. The firm maintains a low profile, which sparks my interest. I noted that WCC is hosting an Elm programming language meet up. What’s interesting is the write up announcing this initiative. I have reproduced some of the lingo used to make this meet up known to the fans of WCC and, of course, Elm:
WCC is excited to host this meetup at her headquarter. Being very interested in the latests software development technology and the advancement of knowledge, we are happy to facilitate this meetup at our offices. Elm is a functional programming language for declaratively creating web browser-based graphical user interfaces.
Anyone can misspell a word. But I particularly liked “her headquarter.” I was expecting “the company’s headquarters.”
Stephen E Arnold, August 10, 2016
The Reach of Cyber Threat Intelligence Companies
August 10, 2016
The social media monitoring complex appears to be gaining a follower. LittleSis News shared an article highlighting their investigative findings, You are being followed: The business of social media surveillance. This post not only reveals the technology companies engaged in surveillance and developing tools for surveillance, those at LittleSis News also filed freedom of information requests to twenty police departments about their social media monitoring. The article concludes with,
“Because social media incites within us a compulsion to share our thoughts, even potentially illegal ones, law enforcement sees it as a tool to preempt behavior that appears threatening to the status quo. We caught a glimpse of where this road could take us in Michigan, where the local news recently reported that a man calling for civil unrest on Facebook because of the Flint water crisis was nearly the target of a criminal investigation. At its worst, social media monitoring could create classes of “pre-criminals” apprehended before they commit crimes if police and prosecutors are able to argue that social media postings forecast intent. This is the predictive business model to which Geofeedia CEO Phil Harris aspires.”
In addition to Geofeedia, the other cyber threat intelligence companies listed are: BrightPlanet, ZeroFOX, Intrado, LifeRaft, Magnet Forensics, Media Sonar Technologies, Signal Corporation Limited. These companies specialize in everything from analyzing deep web content to digital forensics software. Ultimately data is their specialty, not people. These technologies and their applications will undoubtedly stir up questions about the relationship between people, the data they produce on social media, and state actors.
Megan Feil, August 10, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
There is a Louisville, Kentucky Hidden/Dark Web meet up on August 23, 2016.
Information is at this link: https://www.meetup.com/Louisville-Hidden-Dark-Web-Meetup/events/233019199/
Battle of the Maps
August 10, 2016
Once upon a time Mapquest.com used to be the best map Web site on the Internet, then came along Google Maps and then Apple Maps unleashed its own cartography tool. Which is the better GPS tool? Justin Obeirne decided to get to the bottom and find which application is better. He discussed his findings in “Cartography Comparison: Google Maps And Apple Maps.”
Both Google and Apple want their tool to be the world’s first Universal Map, that is the map most used by the world’s population. Google Maps is used by one billion of the world’s population, but Apple Maps has its fair share of users too. These tools are not just mere applications, however, they are powerful platforms deployed in many apps as well.
These maps have their differences: colors, styles, and even different types of maps. The article explains:
“At its heart, this series of essays is a comparison of the current state of Google’s and Apple’s cartography. But it’s also something more: an exploration into all of the tradeoffs that go into designing and making maps such as these. These tradeoffs are the joy of modern cartography?—?the thousands of tiny, seemingly isolated decisions that coalesce into a larger, greater whole. Our purpose here is not to crown a winner, but to observe the paths taken?—?and not taken.”
After reading the article, take your pick and decide which one appeals to you. From my experience, Google Maps is more accurate and prone to have the most updated information. Apple makes great technology, but cartography really is not their strongest point.
Whitney Grace, August 10, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
There is a Louisville, Kentucky Hidden /Dark Web meet up on August 23, 2016.
Information is at this link: https://www.meetup.com/Louisville-Hidden-Dark-Web-Meetup/events/233019199/
Technology: The New Dr. Evil in the Digital Dark Age
August 9, 2016
When I ride my mule down the streets of Harrod’s Creek, I marvel at the young folks who walk while playing with their mobile phones. Heading home after buying oats for Melissa, I look forward to my kerosene lamps.
Technology does not frighten me. I find technology and the whiz kids amusing. I read “Technology Is Now Pop Culture’s Favorite Enemy.” Goodness. I find gizmos and bits fun. The write up suggests that fun loving, top one percenters in education and wealth are finding themselves at the wrong end of a varmint trap.
I find it interesting that technology, which some folks in big cities believe is the way out of a gloomy tunnel, is maybe not flowers, butterflies, and rainbows. (The unicorns have taken to the woods it seems. No unicorns at the moment.)
I learned:
The ubiquitous nature of futuristic technology has lead to an exponential increase in our distrust of each other and the products we use, but most interesting, has taken away some of the blame from government bodies and corporations. We no longer fear agency bodies as much as we fear the physical technology they use.
That seems harsh. I like the phrase, “We’re from the government and here to help you.” Don’t you?
The write up adds a philosophical note:
Despite us being more savvy of how to use social media or despite us having a better understanding of how computers work in general, most of us still aren’t fluent in how it all fits together. We give so much of ourselves over to our devices, and we don’t ask for much in return. When we give something that inanimate that much control over us, it’s terrifying to think that we’re willingly giving up our freedom.
Let’s think about technology in terms of public Web search. One plugs a query into a system. The system returns a list of results; that is, suggestions where information related to the query may be found.
But what is happening is that the person reviewing the outputs does not have to ask, “Are these results accurate? Are they advertising? Are they comprehensive?” There is another question as well, “Is the information objective?” And what about, “Is the information accurate; that is, verifiable?”
The search systems perform another magic trick. The user becomes a content input. This means that the person with access to the queries as a group or the query subset related to a particular individual has new information. In my experience, knowledge is power, and the folks using the search system do not generally have access to this information.
Asymmetry results. The technology outfits offering service have more information than the users. Search does more to illuminate the dark corners of those using the search system than the results of a search illuminate the user’s mind.
Without the inclination to figure out what’s valid and what’s not or lacking the expertise to perform this type of search results vetting, the users become the used.
That sounds philosophical but there is a practical value to the observation. Without access and capability, the information presented becomes a strong influence on how one thinks, views facts, and has behavior influenced.
My thought is, “Welcome to the medieval world.” It is good to be a king or a queen. To be an information peasant is the opposite.
Giddy up, Melissa. Time to be heading back to the digital hollow to think about the new digital Dr. Evil.
Stephen E Arnold, August 9, 2016
Big Consulting Firm Smashes the Big Data Conundrum
August 9, 2016
I read “Cracking the Data Conundrum: How Successful Companies Make Big Data Operational.” The high level, super sophisticated, MBA quivering report is free. Does that mean that Capgemini Consulting is trying to drum up business? I thought these top level outfits generated 90 percent of their annual revenue from repeat business? Perhaps today’s economic climate is different?
The report is interesting because the premise is that Capgemini has solved a “conundrum.” This is a nifty word which I learned when I was a wee lad trying to keep my tutor in Campinas, Brazil, happy. I recall that the word was used by one Thomas Nash (no, not a relative of the Nash made famous with the quip “the golden trashery of Ogden Nashery). But that neologistic meaning has a fresh charge of meaning for me; to wit:
A term of abuse for a crank or a pedant.
Today the word is popular among the MBA set as a solvable problem. However, a conundrum can be another word for dilemma. That’s a logical word for illogical statements; for example,
Bruno was gored on the horns of a big, angry dilemma.
What does the Capgemini document suggest is the resolution to the problem of Big Data.
The write up tells the reader that most outfits trying to integrate Big Data into every day work life screw up. The fancy wording is:
Successful Big Data implementations elude most organizations.
That’s bad for the organizations, and I assume really good for consultants who know how to deal with wasted money.
The problem? Organizations’ management are not able to manage. I learned:
Our research revealed that the top challenges that organizations face include: dealing with scattered silos of data, ineffective coordination of analytics initiatives, the lack of a clear business case for Big Data funding, and the dependence on legacy systems to process and analyze Big Data.
Imagine organizations have these flaws. What are they to do?
Step one is to get their act together; that is, organize for Big Data. Sounds good. But what if the organization is set up to do something else; for instance, make men’s shirts or do publicity of a Hollywood motion picture?
Well, these outfits need to have a systematic approach to Big Data. And one size does not fit every organization. Capgemini identifies four ways to put the ponies in the circus wagon. These are:
- Scattered pockets of Big Data stuff
- Decentralized Big Data stuff. (How is this different from “scattered pockets”?)
- Centralized Big Data stuff
- A Big Data business unit. (This is the one that delivers the most “success.” I am not sure for whom however.)
How does an organization move from total loser in Big Data to a successful outfit integrating Big Data into operations? This effort, which will be billed either as a flat fee, a retainer, or time and materials basis, is an “implementation journey.” I have a hunch that this trip will not a 10 walk to the convenient store for a bottle of Big Red soda pop. The trip will be a hike through the Ural mountains in winter.
The write up includes a test. This makes it easy for the shirt maker in Bangladesh or the 20 somethings working from a trailer in Orange County to put their act in the circus’ center ring.
The write up references a survey conducted in 2014. I suppose in the slow moving world of the shirt makers and Hollywood publicists a year and a half is a reasonable time interval.
If you want to test your understanding of the word “conundrum,” you will want to read this free report. Only you can answer this question: Does conundrum reference a crank or pedant or a hapless MBA dangling from a sharp horn? Whenever horns of a bull enter a conversation, other stuff may follow.
Stephen E Arnold, August 9, 2016
Facebook Algorithms: Doing What Users Expect Maybe
August 9, 2016
I read an AOL-Yahoo post titled “Inside Facebook Algorithms.” With the excitement of algorithms tingeing the air, explanations of smart software make the day so much better.
I learned:
if you understand the rules, you can play them by doing the same thing over and over again
Good point. But how many Facebook users are sufficiently attentive to correlate a particular action with an outcome which may not be visible to the user?
Censorship confusing? It doesn’t need to be. I learned:
Mr. Abbasi [a person whose Facebook post was censored] used several words which would likely flag his post as hate speech, which is against Facebook’s community guidelines. It is also possible that the number of the words flagged would rank it on a scale of “possibly offensive” to “inciting violence”, and the moderators reviewing these posts would allocate most of their resources to posts closer to the former, and automatically delete those in the latter category. So far, this tool continues to work as intended.
There is nothing like a word look up list containing words which will result in censorship. We love word lists. Non public words lists are not much fun for some.
Now what about algorithms? The examples in the write up are standard procedures for performing brute force actions. Algorithms, as presented in the AOL Yahoo article, seem to be collections of arbitrary rules. Straightforward for those who know the rules.
A “real” newspaper tackled the issue of algorithms and bias. The angle, which may be exciting to some, is “racism.” Navigate to “Is an Algorithms Any Less Racist Than a Human?” Since algorithms are often generated by humans, my hunch is that bias is indeed possible. The write up tells me:
any algorithm can – and often does – simply reproduce the biases inherent in its creator, in the data it’s using, or in society at large. For example, Google is more likely to advertise executive-level salaried positions to search engine users if it thinks the user is male, according to a Carnegie Mellon study. While Harvard researchers found that ads about arrest records were much more likely to appear alongside searches for names thought to belong to a black person versus a white person.
Don’t know the inside rules? Too bad, gentle reader. Perhaps you can search for an answer using Facebook’s search systems or the Wow.com service. Better yet. Ask a person who constructs algorithms for a living.
Stephen E Arnold, August 9, 2016
These Emojis Are Logical
August 9, 2016
Emojis are a secondary language for many people, especially the younger sect, and whole messages can be conveyed within a few images. Someone needs to write an algorithm to translate emoji only messages, but machine learning has not yet reached the point where it can understand all the intricacies associated with emojis. Or has it? TechCrunch shares that “Dango Mind-Melds With Emoji Using Deeping Learning And Suggests Them While They Type.”
Dango is an emoji suggestion chatbot. Unlike the Microsoft chatbot that became anti-Semitic and misogynist in a matter of hour, Dango just wants to give you emoji suggestions to pep up your messages:
“Okay, so Dango is one of those virtual assistants that lives in your chat apps, and this one is based on a neural network that has been trained with millions of examples to understand what emoji mean. So not only can it suggest an appropriate one, but it can translate entire sentences. Its icon is a weird piece of cute cake, which sits above your keyboard watching you type. It’s free for Android right now, with an iOS version coming out eventually.”
Aww, it’s a little cake icon that sits above your keyboard. Is it not tempting already to download it make Dango your friend? The cute factor comes after the deep machine learning took place.
The Dango programmers used a recurrent neural network to teach Dango how to decipher the meaning of emoji. It would guess, then check against real world examples, then adjust its parameters when it was wrong. The guesses were assembled in a “semantic space” that relates the emojis to concepts (check the article for the visualization).
Dango is constantly updating itself to be on top of the latest slang and memes, including the negative aspects of the language. Dango is still learning, especially when it comes to translating entire sentences to pictures. Before you say that the written language cannot be replicated in little images, it was done eons ago by Egyptians, Sumerians, Phoenicians, and still by the Chinese, Japanese, and other Asian cultures.
Whitney Grace, August 9, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
There is a Louisville, Kentucky Hidden /Dark Web meet up on August 23, 2016.
Information is at this link: https://www.meetup.com/Louisville-Hidden-Dark-Web-Meetup/events/233019199/
Beyond Search HonkinNews Video for 8 August 2016 Online Now
August 9, 2016
You can view the August 8, 2016, HonkinNews program at this link. The video comes from Goodwill-grade 8 mm film equipment. The program highlights recent stories from the free (yep, no cost whatsoever) Beyond Search Web log. Learn about the how one Google executive “escaped” life in the fast lane. The Verizon acquisition of Yahoo reminds Stephen of Washington’s wooden false teeth. The deal allows Verizon to own two Internet artifacts. Hewlett Packard Enterprise, owner of Autonomy, faces an uncertain future as its sells units and thinks about selling itself. And there’s more in the six minute news program; for example, a restrained MBA cheer for Big Data. But that’s a sotte voce rah, rah. Like Beyond Search, the honking video version tries to separate the giblets from the goose feathers in the thrilling world of search, content processing, and related disciplines. That’s not easy in today’s search-centric world where relevance is mostly good enough and jargon is its own virtual reality.
Ken Toth, August 9, 2016
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